Have you heard the saying “if you can’t measure it, you can’t manage it”? The amount of data available to the population is at an all time high. Clients, employers, associates and other companies research us, form opinions on us, and decide whether they want to work with us. Why can’t we do the same thing with them? We can.
Data mining is known to some as “knowledge discovery” dating back to the 18th century. It can be defined as the process in which we find trends and patterns in large amounts of data to be used in the future to improve strategy or to understand the needs of our clients better. Why do we want to find patterns or trends? Because it takes our business to the client and increases our bottom line by saving costs in areas such as marketing and more cost-effective corporate real estate strategies to make proactive knowledge-driven decisions. Data mining provides models that are both descriptive and prospective to help address why things happen and what might happen in next or in the future. It can find opportunities for improvement and offer better planning for future projects. Data mining offers a way to find prospective clients, maximize the utilization of advertising by targeting key areas to market, and to better predict their behaviors. It can even identify high-risk clients, profitable and unprofitable customers or identify fraud or unusual behavior. By using this information, companies are able to save time and money by targeting their exact audience at the exact place.

To better gauge businesses, the data collected from mining use key performance indicators “KPIs” such as revenue, cost targets, profit targets, number of customers, and employee turnover rates (to name just a few). These key performance indicators drive business performance and productivity by analyzing the data and applying the information to changes or updates in business plans. What gets measured gets done. Many companies use the data collected to generate more sales. For example, Amazon.com uses data mining to dig deeper into understanding their customer’s buying patterns. Based on previous purchases, Amazon.com was able to add additional purchase suggestions for their buyers. Amazon.com was able to increase their sales by 15%.

In marketing to our clients, we need to know: Where are the leads coming from? Where should we put our ads? What kind of people are responding? For apartment owners, for example, this information can be invaluable. The three main things renters search for when looking for apartments: They want to know how many bedrooms, how much will it cost, and what area will they be living in? What they REALLY want to know is: What kind of people live there? Would they fit in? More agencies are using the availability of technology to collect data about habits and status to present an almost V.I.P. list to target, cutting down on time spent.

The most effective way to begin the data mining process is to create a goal statement. Are you looking to “attract better tenants” or maybe you want to “predict the likelihood that a commercial tenant will have a late payment within the next 6 months”? The ability to save your clients time and money is a great skill not just in commercial real estate but also as a business strategy in your company.

Real estate data and analytics should be considered an essential component of how companies make capital investment and occupancy decisions to improve their overall productivity, according to some experts, helping to deliver results, decrease spending and increase productivity. Data mining can be as simple or as complex as you choose. The advantages, if done correctly, include better customer service, better productivity from your team, better target marketing campaigns. It’s your call to make, but let me tell you now, that this will give you an edge up on your competition that isn’t using data mining in their business strategy. In short, this can be applied anywhere in your business plan, take the reigns now and take control of your market. Though real estate is the last to adopt the use of data mining, the time has come where you need to do it or if you don’t, you will be left in the dust.